From 1G to 5G, passing through Universal Mobile Telecommunication Systems (UMTS) and Long Term Evolution (LTE) innovations, each generation of mobile technology has been designed to meet the needs of network operators and final consumers. 5G, in particular, is making a significant step towards developing a low latency tactile access network, by providing new additional wireless nerve tracts, i.e., data pipes. Yet, nowadays societies are becoming ever more data-centric, data-dependent and automated, and will introduce increasingly more stringent requirements (in terms of ultra-high reliability, capacity, energy efficiency, and low latency) which may saturate the capacity of traditional technologies for wireless systems. We make the case that sixth generation (6G) systems will contribute to fill this gap. In particular:

• 6G will foster the Industry 4.0 revolution, i.e., the digital transformation of industrial manufacturing, though breakthrough advancements in the field of semiconductor and integrated circuit, and will drive radical automation of productivity.
• 6G will accelerate the adoption of solutions for smart cities, targeting life quality improvements, environmental monitoring and city management automation through support for user-centric machine to machine communication and energy harvesting. 6G will also promote technological advancements in the field of virtual/augmented reality and holographic telepresence.
• 6G will revolutionize the health-care sector through innovations like mobile edge computing, virtualization and artificial intelligence, and will eliminate time and space barriers through remote surgery and healt-care workflow optimizations.
• 6G will pave the way for the coming era of connected and autonomous vehicles and flying vehicles, e.g., drones, offering the potential of safer traveling, improved traffic management, and support for infotainment applications through advances in hardware and software as well as pioneering connectivity solutions.
• 6G technologies will encompass capacity expansion strategies to offer massive-scale connectivity to the users, even when civil communication infrastructures may be compromised (e.g., in case of emergency or disaster situations).The broad purpose of this paper is to understand how future 6G systems can be developed to meet the demands for a fully connected, intelligent digital world. We overview emerging technologies and developments at all layers of the protocol stack, from core physical communication methods to networking design and deployment, that have significant promise for future 6G systems.

6G ENABLING TECHNOLOGIES

A new generation of mobile networks is generally characterized by a set of novel communication technologies that provide unprecedented performance (e.g., in terms of available data rate, latency) and capabilities. For example, massive Multiple Input, Multiple Output (MIMO) and mmWave communications are both key enablers of 5G networks. In order to meet the requirements previously described, 6G networks are expected to rely on conventional spectrum (i.e., sub-6 GHz and mmWaves) but also on frequency bands that have not been considered yet for cellular standards, namely the terahertz band (which can be exploited to allocate a massive amount of bandwidth to close range and massively beamformed communications) and Visible Light Communications (VLC) (which could provide network operators a cost-effective and practical way to improve indoor coverage). Besides the new spectrum, 6G will also transform wireless networks by leveraging a set of technologies that have been recently enabled by advancement in physical layer and circuits research, but are not part of 5G. We expect 6G to (i) integrate full-duplex capabilities in the communication stack, to enable continuous downlink transmission with simultaneous uplink acknowledgments or control messages (or vice versa), and increase the multiplexing capabilities and the overall system throughput without using additional bandwidth; (ii) exploit novel channel estimation techniques, e.g., out-of-band estimation and compressed sensing, to increase the efficiency of the 6G control plane; and (iii) combine communication with sensing and network-based localization capabilities, to improve control operations and provide novel user services.

The disruption brought by these communication technologies will enable new 6G network architectures, but also potentially require structural updates with respect to current mobile network designs. For example, the density and the high access data rate of terahertz communications will create constraints on the underlying transport network, which has to provide both more points of access to fiber and a higher capacity than today’s backhaul networks. In this context, we envision the introduction and/or deployment of the following architectural paradigms:

• cell-less architecture, with tight integration of multiple frequencies and communication technologies, to guarantee a seamless mobility support and exploit the complementary characteristics of different frequency bands, e.g., the sub-6 GHz layer for control, and terahertz link for the data plane;
• disaggregation and virtualization of the networking equipment, including the lower layers of the protocols stack (e.g., physical and MAC layers), to decrease the costs of networking equipment and make massively dense deployment economically feasible;
• advanced access-backhaul integration, to cope with the massive increase in the density of access points;
• energy-harvesting strategies for low-power consumption network operations, to make 6G devices more efficient and lessenergy consuming with respect to current ones.
  Finally, the complexity of communication technologies and network deployments will probably prevent closed-form and/ormanual optimizations. While the application of intelligent techniques in cellular networks is already being discussed in the 5G domain, we expect 6G deployments to be much denser (i.e., in terms of number of access points and users), heterogeneous (in terms of integration of different technologies), and with stricter requirements in terms of performance with respect to 5G. Therefore, the intelligence will play a more prominent role in the network, going beyond classification and prediction tasks which are being considered for 5G systems. Notice that the standard may not specify the techniques and learning strategies to be deployed in networks, but data-driven approaches can be seen as tools that network vendors and operators can use to meet the 6G requirements.

Millimeter wave (mmWave) communications are expected to enable increased data rates in future wireless systems. Unfortunately, at such high frequencies (3 – 300GHz) path-loss increases and the range or received power decreases, making beamforming and the use of large antenna arrays a necessity. However, large antenna arrays with a wide bandwidth may have high power consumption, especially in the analog to digital converters (ADC) of the receiver. Power consumption of an ADC increases linearly with bandwidth and exponentially with the number of bits, and therefore becomes the main constraint to mmWave array receiver technologies.

The receiver architectures to reduce power consumption in the literature are separated in three families:

1. Analog Combining (AC) relies on a single Radio-Frequency (RF) chain and ADC. AC consumes the least power and is an attractive choice whenever more versatile digital processing is not really necessary.
2. Hybrid Combining (HC) performs combining in both the analog and the digital domains to reduce the number of RF chains and ADCs while still allowing some spatial multiplexing.
3. Digital Combining (DC) with low-resolution ADCs (for example, 1-4 bits) maintains the advantages of a digital MIMO architecture while increasing the quantization error.

Our research is mostly focused on the trade-off between spectral efficiency (SE) and energy efficiency (EE) for AC, HC and DC receiver architectures. We considered quantized receivers and identify how the spectral and energy efficiency trend is related to the number of ADC bits at the receiver. The results showed that there is an optimal number ADC bits (roughly 3-5) that maximizes the energy efficiency. Our research also highlighted that the general perception regarding high energy consumption of a fully digital receiver is not true in general. Rather, there are regimes where DC outperforms AC and HC. However, EE trend between AC, DC, and HC schemes is strictly dependent on the components power consumption values, the number of spatial streams supported by the channel and the number of RF chains for HC. To address this issue, we also developed a web tool where the reader may generate a (SE vs EE) chart reproducing our analysis method using any other component parameter values.

Web tool link: http://enigma.det.uvigo.es/_fgomez/mmWaveADCwebviewer/

In addition, we propose a further improvement (in terms of power consumption) to the fully-digital low-resolution strategy by studying the possibility of enabling a variable number of bits in each ADC of the DC system. Compared to a conventional approach to low-resolution DC, where each RF chain has equal ADCs with the same fixed number of bits b_ref , we propose to assign some ADCs a slightly higher number of bits b_high > b_ref , while the rest of the RF chains have an even lower number of bits (b_low < b_ref ). Our results show that the same capacity of the fixed-bit system can be achieved using two variable-bit values with a power saving between 20 and 80%, depending on the link pre-quantization Signal to Noise Ratio (SNR) and the corresponding selection of b_high and b_low.

This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No. 704837 [Marie Skłodowska-Curie Individual Fellowship].

Due to the high path loss attenuations, MIMO systems with beamforming techniques are essential to ensure an acceptable range of communication in mmWave networks. In particular, the use of antenna arrays for future mobile scenarios is fundamental in order to create a beam in the direction of the user equipment. Therefore, increasing the gain of the transmission. Among the possible antenna array designs, the most suitable approach is the use of uniform planar arrays (UPA). In this configuration, the antenna elements are evenly spaced on a two-dimensional plane and a 3D beam can be synthesized.

In order to precisely evaluate mmWave scenarios, it is important to consider realistic and accurate radiation models. Related works in the literature characterize the antenna array either over-simplifying its gain with piece-wise functions, or modeling it as an array of isotropic transmitting sources. At high frequencies (e.g., mmWave bands), where high attenuations are present, quantifying the actual antenna gain obtained due to the radiation pattern is fundamental in order to precisely evaluate any mmWave system.

The radiation model proposed by the 3GPP can be used to address this issue. This model precisely simulates the radiation pattern of a patch antenna element assuming large attenuation for lobes in the opposite plane of transmission. In our works, motivated by the need to properly capture mmWave propagation behaviors and understand the achievable performance (e.g., capacity in 5G cellular scenarios), we aim at accurately characterizing the antenna radiation pattern.

Our results show how the performance changes with the radiation pattern used. Consequently, it is crucial to use an accurate and realistic radiation model for proper performance assessment and system dimensioning.

Despite our preliminary studies, a lot of research activity is still required in the optimization of array radiation components such as the spacing of the elements, the amplitude and the phase vectors of each antenna element.

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The millimeter wave bands offer orders of magnitude more spectrum than conventional wireless frequencies but, on the other hand, suffer from increased pathloss, severe channel intermittency and inability to penetrate through solid materials. To overcome these issues, future networks must establish highly directional transmission links, typically formed with high-dimensional phased arrays, to benefit from the resulting beamforming (BF) gain and recover a sustainable quality of service.

In this context, the definition of new control layer procedures is critical and is particularly challenging for initial access (IA), which allows a mobile user equipment (UE) to establish a physical link connection with a base station (BS), a necessary step to access the network.

In current LTE systems, IA is performed on omnidirectional channels, whereas beamforming or other directional transmissions can only be performed after a physical link is established. On the other hand, in order to overcome the increased isotropic pathloss experienced at higher frequencies, in next-generation 5G systems a mechanism by which the BS and the UE determine suitable initial directions of transmission must be determined. However, directionality can significantly delay the cell search and access procedures, which is a particularly sensitive issue in 5G networks, and thus motivated us to identify and study some performance trade-offs in terms of delay, coverage, and overhead.

In our works, we investigated various IA schemes and we compared the performance of these approaches in terms of both misdetection probability and discovery time, under overhead constraints and different channel conditions. Specifically, we focused on:

1. Exhaustive search, a brute-force sequential beam searching technique in which both users and base stations have a predefined codebook of directions that cover the whole angular space and are used sequentially to transmit/receive.

2. Iterative search, a two-stage scanning approach in which, in the first phase, the BS transmits pilots over wider sectors while, in the second phase, it refines its search within the best such sector by steering narrower beams.

3. Context Information-based search, in which users are informed about the geolocations of surrounding mmWave BSs through an LTE link, with the goal of reducing the angular directions to investigate in the initial access phase.

We argued that there is a trade-off between IA latency and misdetection probability: compared to exhaustive schemes, iterative techniques require less time to perform the angular search, but exhibiting higher misdetection probabilities in general, as wider beams provide reduced gains. Moreover, the misdetection probability of pure Context Information-based approaches may be higher than for an exhaustive approach if the direct path does not correspond to good channel conditions (i.e., in NLOS or multi-path scenarios), since the beam chosen by the UE may be suboptimal.

The 5th generation (5G) of wireless communications will be characterized by very stringent requirements in terms of latency, jitter and reliability, and is expected to provide the users with unprecedented data rates. In this context, the millimeter wave (mmWave) bands above 10 GHz have gained great attraction thanks to the very large bandwidths available at such high frequencies (up to 400 MHz per carrier, according to the latest 3GPP NR specifications). The severe isotropic path loss and the harsh propagation characteristics of the mmWave environment, however, demands a dense base station deployment to guarantee line-of-sight links at any given time and decrease the outage probability. Nonetheless, such a deployment will be inevitably costly for network operators and, as a result, more economically sustainable solutions have been recently investigated by the 3GPP as part of the Integrated Access and Backhaul  (IAB) Study Item (SI).

According to the 3GPP aggreements, NR cellular networks with IAB functionalities will be characterized by (i) the possibility of using the mmWave spectrum; (ii) the integration of the access and backhaul technologies, i.e., using the same spectral resources and infrastructures to serve both mobile terminals in access as well as the NR gNBs in backhaul; (iii) the possibility of deploying plug-and-play IAB nodes capable of self-configuring and self-optimizing themselves.

Along these lines, in our research we extended the capabilities of the existing mmWave module for ns-3 (which already models the mmWave channel, and features a 3GPP-like protocol stack tailored for mmWave cellular networks) to support advanced IAB functionalities. This extension can support both single and multi-hop IAB deployments, autonomous network configuration, and features new scheduling mechanisms that support the sharing of access and backhaul resources.

We also designed distributed backhaul path selection policies to efficiently forward the backhaul traffic (possibly through multiple hops) from a wireless gNB (i.e., the NR term for a base station) to a wired gNB connected to the core network. We investigated (i) an Highest-Quality-First (HQF) policy which always selects, as a parent, the gNB with the highest quality, (ii) a Wired-First (WF) policy which always selects the wired gNB, if available, and (iii) a Position-Aware (PA)  policy that selects the link with the highest SNR among those with parents which are closer to a wired gNB. The considered policies may or may not leverage on a Wired Bias Function (WBF) that biases the link selection towards base stations with wired backhaul capabilities, to minimize the latency of the relaying operations.

Finally, current cellular systems achieve spatial multiplexing rate gains in the physical layer through Multi-User MIMO (MU-MIMO) techniques. We have proposed and analyzed a model for long term throughput-optimal scheduling and rate control for arbitrary MU-MIMO mesh networks using the Network Utility Maximization (NUM) Maximum Back Pressure framework. We used this model to evaluate the capacity of multi-hop mmWave picocellular mesh networks with IAB under an abstract type of NUM-optimal scheduling. We found that over a simulation campaign the introduction of MU-MIMO physical layer techniques, mesh topologies and multi-attachment enabled a theoretical 150% increase in network capacity. Part of our ongoing work is the study of the feasibility of these theoretically-predicted gains in practical cellular standards.

LIST OF RELATED PUBLICATIONS

This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No. 704837 [Marie Skłodowska-Curie Individual Fellowship].

A fundamental and outstanding question for the design of mmWave networks is to understand the effects of interference and, more specifically, under which circumstances mmWave cellular networks are likely to be limited by interference or by thermal noise. Identifying in which regimes networks operate is important to design the system. For example, while interference limited networks can benefit from advanced techniques such as inter-cellular interference coordination, coordinated beamforming and dynamic orthogonalization, these techniques have little value in networks where thermal noise, rather than interference, is dominant.

In traditional cellular deployments, in particular macrocell-based networks, the relative power of interference to thermal noise is a function of the distance between cells and of the transmit power spectral density. Differently, the results in our study demonstrate that in mmWave systems the relative strength of undesired signals depends on many more factors.

Most importantly, mmWave systems rely on highly directional transmissions to overcome the high isotropic path loss. Directional transmissions tend to isolate users, thereby reducing the interference. However, the degree of isolation depends strongly on the size of the antenna arrays, the antenna pattern, and the level of local scattering and spatial multipath. In addition, mmWave signals can be blocked by many common materials, eliminating long distance links. This potentially improves the isolation but may also lead to coverage holes. There are also significant differences in path loss for mobiles in Line-of-Sight and Non-Line-of-Sight locations.

To precisely design mmWave systems, it is important to examine mmWave regime under large-scale deployments. For this purpose, we study scenarios that apply both an accurate mmWave channel model, derived from experiments, and accurate beamforming pattern, into an analytical framework based on stochastic geometry. In this way we can obtain metrics of interest in large-scale mmWave cellular networks.

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The performance in mobility scenarios currently prevents mmWave from being used in cellular networks. Indeed, as described here, mmWave links suffer from blockage from obstacles such as the human body, vehicles, buildings, etc. Moreover, mmWave cells will cover a small area, and require a dense deployment. As the user moves, it may suddenly lose the connectivity to the current mmWave base station. It may even be in outage with respect to all of the cells. The mobility management under these hypothesis becomes challenging: the number of handovers and/or beam switch events increases, and the solutions adopted in traditional networks are not enough. Indeed, if the mobile terminal connects to a single Radio Access Network at any given time, an outage event would require a Radio Link Failure or a long and complex inter-RAT handover, for example to a legacy LTE network.

We propose a mobility management solution which relies on dual connectivity. The mobile user connects to an LTE and a mmWave base station at the same time. Moreover, a local mobility anchor coordinates each group of mmWave base station. Therefore, there is no need to interact with the core network for local mobility. The user plane is split at the PDCP layer.

This architecture makes it possible to:

• Collect channel measurements and track the optimal base station for each mobile user;
• Design faster network procedures, to quickly switch from LTE to mmWave and viceversa, and to perform a swift secondary cell handover without any interaction with the core network.

The dual connectivity architecture was analyzed with a first-of-its-kind simulation campaign. It combined a mmWave dynamic channel model and end-to-end TCP/IP and cellular network protocol stacks, using the tool described in the Simulation page. The channel model used experimental traces to model the transition between LOS and NLOS and vice versa. Our architecture is able to better adapt to the dynamic mmWave channel conditions than a traditional single connectivity solution. Therefore, it obtains a lower latency and smaller throughput variations. This increases the robustness of the network, enhancing the quality of experience of the mobile user.

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Simulation is an essential tool that enables the performance analysis and the design of end-to-end networks. It indeed provides insights on complex behaviors that are hard to model analytically. Moreover, using an end-to-end simulator, a researcher can study in detail the interaction among the different elements of the network, at different layers in the protocol stack.

Therefore, our team at the University of Padova and NYU WIRELESS have developed an end-to-end simulation framework for 5G mmWave networks. It is based on ns-3, a popular and open-source network simulator. As a results, this simulator allowed us to perform the studies described in the Transport Protocols and Mobility sections. For example, it features:

• multiple channel models, including the implementation of the latest 3GPP model for frequencies above 6 GHz and the possibility of plugging traces from ray tracing softwares;
• detailed PHY and MAC layers, with customizable parameters that can also simulate different numerologies;
• Carrier Aggregation;
• 3GPP-like RLC, PDCP, RRC and core network elements, that extend the LTE implementation of ns-3;
• support for mobility via Dual Connectivity;
• ns-3 full TCP/IP stack and possible integration with the Linux TCP/IP stack.

This paper (link) provides a complete description of the ns-3 mmWave module.

Download the end-to-end mmWave simulator

Recently, we published an extension which supports the simulation of wireless relays through Integrated Access and Backhaul. This page describes our research effort in the IAB area.

Download the Integrated Access and Backhaul (IAB) simulator

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While spectrum at millimeter-wave (mmWave) frequencies is less scarce than at traditional frequencies below 6 GHz, still it is not unlimited. In particular if we consider the requirements from other services using the same band and the need to license mmWave bands to multiple mobile operators. Therefore, an efficient use of the spectrum is critical to harvest the maximum benefit from emerging mmWave technologies. Moreover, for the first time standardization alliances will be studying the development of a cellular technology operating solely (in a stand-alone mode) in unlicensed spectrum.

In this section, we discuss resource sharing, a key dimension in mmWave network design in which spectrum, access and/or network infrastructure resources can be shared by multiple operators. It is argued that this sharing paradigm will be essential to fully exploit the tremendous amounts of bandwidth and the large number of antenna degrees of freedom available in these bands. Also to provide statistical multiplexing to accommodate the highly variable nature of the traffic.

In our works, we have investigated and compared various sharing configurations in order to capture the enhanced potential of mmWave communications.

Our results reflect both the technical and the economical aspects of the various sharing paradigms. We deliver a number of key insights, corroborated by detailed simulations, which include an analysis of the effects of the distinctive propagation characteristics of the mmWave channel, along with a rigorous multi-antenna characterization. Key findings of our study include: firstly the strong dependence of the comparative results on channel propagation and antenna characteristics, and therefore the need to accurately model them, and second the desirability of a full spectrum and infrastructure sharing configuration, which may result in increased user rate as well as in economical advantages for both service provider.

We have also introduce a new hybrid spectrum access scheme for mmWave networks, where data packets are scheduled through two mmWave carriers with different characteristics. In particular, we consider the case of a hybrid spectrum scheme between a mmWave band with exclusive access and a mmWave band where spectrum is pooled between multiple operators. This approach provides advantages with respect to traditional fully licensed or fully pooled spectrum access schemes.

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A seamless interaction between mmWave cellular networks and transport protocols (e.g., TCP) will be the key to fully exploit the resources available at mmWave frequencies. Most of the research on mmWave, however, has focused so far on the channel and the PHY and MAC layers. Therefore, the performance of transport protocols over this kind of links is still relatively unexplored.

In particular, mmWave links are characterized by wide variations in the offered rate with LOS/NLOS transitions. Moreover, the link may be in outage if all the reflections in NLOS are blocked, and packets may be lost. This motivates the introduction of link-layer retransmissions (time diversity), and large buffers to avoid packet losses. We showed that without retransmissions it is not possible to sustain a high TCP throughput in NLOS conditions. However, this also increases the end-to-end latency. Moreover, the undesired consequence is the emergence of the bufferbloat phenomenon, which has a negative impact on both the throughput and the latency. Finally, if there is an extended outage, the loss of multiple packets may trigger a retransmission timeout. In this case, we showed that state-of-the-art TCP congestion control algorithms may require a long time to reach full bandwidth utilization, thus wasting resources.

The performance of the end-to-end connection can be improved using path diversity with Multipath TCP (MP-TCP) on combined LTE and mmWave links. However, we showed that also in this case the available congestion control algorithms cannot fully exploit the resources available in the combined links. Moreover, the distance between the mobile user and the base station affects the choice of the best combination of paths. Indeed, at large distance it is better to couple a mmWave link with a reliable LTE sub-6 GHz link than with another mmWave link, despite the difference in bandwidths.

The use of cross-layer information is another promising approach. In fact, it makes it possible to break the abstract view that TCP has of the end-to-end connection. Moreover, it increases the responsiveness of the protocol to sudden changes in the link quality. We proposed a cross-layer congestion control algorithm (X-TCP) to improve the performance of TCP in uplink scenarios. X-TCP adapts the congestion window with information related to the mmWave channel, and showed a performance gain in both throughput and latency with respect to TCP CUBIC in randomly generated scenarios.

LIST OF RELATED PUBLICATIONS

Millimeter-wave signals suffer from increased pathloss, severe channel intermittency, and inability to penetrate through most common materials, thus making the propagation conditions more demanding than at lower frequencies. To overcome these issues, next-generation cellular systems must provide a mechanism by which users and mmWave base stations establish highly directional transmission links to recover a more sustainable communication quality. In this context, directional links require fine alignment of the transmitter and the receiver beams, an operation which might dramatically increase the time it takes to access the network. Moreover, the dynamics of the mmWave channel imply that the directional path to any cell can deteriorate rapidly, necessitating the need for intensive tracking of the mobile terminal.

Therefore, periodical monitoring of the channel quality between each UE-mmWave eNB pair, to perform a variety of control tasks (including handover, path selection, radio link failure detection and recovery, beam adaptation), is fundamental to provide efficient mobility-management schemes.

The tracking of the downlink channel quality is relatively straightforward in 3GPP LTE and is based on the cell reference signal (CRS) that is continuously and omnidirectionally sent from each eNB. However, a CRS will likely not be available in mmWave systems, since downlink transmissions at mmWave frequencies will be directional and specific to the user.

For this reason, in our work, we proposed an uplink measurement system to perform fast beam realignment and/or handover.  This scheme was based on multi-connectivity (MC), to benefit from both the high capacities of mmWave channels, as well as from the more robust, but lower capacity, sub-6 GHz links. We demonstrated that the uplink control signaling enables the network to track the angular directions of communication to the UE on all possible links simultaneously, so that, when a paths witch is necessitated, no directional search needs to be performed (this approach greatly saves switch time, since directional scanning dominates the delay in establishing a new link). Additionally, in the case when the mmWave links are not available, the network is able to send the scheduling and serving cell decisions over the LTE cells, since legacy bands are almost transparent to obstacles. Such multi-frequency control signaling can be exploited to implement more robust and stable resource allocation and network management.

We also presented an innovative tracking technique by which the UE can alternate exhaustive scans of the whole angular space (i.e., to determine the optimal surrounding mmWave eNB to connect to, and eventually trigger a handover event accordingly) to more frequent (and faster) refinements operations (i.e., to adapt the beam if the previously optimal configuration has degraded).  We argue that the proposed procedure is particularly suited to highly variant and unstable environments, or as a support to the legacy tracking operations when frequent complete angular sweeps are not executable.

Further work is still needed. In particular, due to the lack of temporally correlated mmWave channel measurements, it is currently not possible to develop an accurate analytical model for mobility-related scenarios, which on the other hand remains a very interesting and relevant item for future research.

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In recent years, communication between vehicles (V2V) and between vehicles and infrastructure (V2I), cumulatively indicated as V2X, has been investigated as a means to support basic automotive applications, like cruise control, blind spot detection, parking assistance and so on. Currently, the V2V communication protocol is the so-called dedicated short-range communication  (DSRC), which provides a nominal coverage range of about 1 km, with achievable data rates in the order of 2-6 Mbps. V2I communication, instead, makes use of the 4G-LTE connectivity below 6 GHz, enabling a data rate of up to 100 Mbps in high mobility scenarios.  These technologies, however, will not be able to support the massive demand for high data rates that is expected to be required by the next generation of automotive applications, which will include advanced services based on a number of sophisticated sensors (e.g., radars, cameras, LIDARS), to support higher layers of automated driving (e.g., object recognition,object classification, obstacle avoidance).

A possible answer to this growing demand for ultra-high transmission speeds in vehicular networks can be found in the millimeter wave bands which, however,  are subject to high signal attenuation and challenging propagation characteristics.

Therefore, in our works, we started investigating the limits that prevent the direct employment of the existing V2X communication protocols on mmWave links, including:

• Overhead: In current V2X communication technologies, transmissions are mostly omnidirectional while mmWave links are typically directional, to overcome the isotropic pathloss experienced at high frequencies. However, directional links may require precise alignment of the transmitter and receiver beams, an operation which may increase the latency of the communication.
• High mobility: A suitable beam pair may not last long enough to allow the completion of a data exchange, due to the high speed of the nodes, thus resulting in transmission errors. Moreover, the increased Doppler effect could make the assumption of channel reciprocity not valid and could impair the feedback over mmWave links, which is a potential point of failure for beam sweeping.
• Blockage: While signals at lower frequencies can penetrate more easily through buildings, mmWave signals do not penetrate most solid materials. As a result, an obstacle can jeopardize a successful communication even if the automotive nodes are perfectly
• Channel model: Available measurements at mmWaves in the V2X context are still very limited, and realistic scenarios are indeed hard to simulate. In fact, the increased reflectivity and scattering from common objects and the poor diffraction and penetration capabilities of mmWaves are the main factors preventing the existing lower frequency channel models from being used for an automotive mmWave scenario. Moreover, current models for mmWave cellular systems present many limitations for their applicability to a V2X context, due to the more challenging propagation characteristics of highly mobile vehicular nodes.

We also highlighted possible solutions at the PHY and MAC layers to enable automotive networks to operate at mmWaves and, through a preliminary connectivity and throughput analysis, we showed that the performance of the automotive nodes in highly mobile mmWave scenarios strictly depends on the specific environment in which the vehicles are deployed, and must account for several automotive-specific features such as the vehicle’s speed, the beam tracking periodicity, the node density and the MIMO antenna configuration.

Download here our poster “Coverage and Connectivity Analysis of Millimeter Wave Vehicular Networks”: